Edit model card

mnist-digit-classification-2022-09-04

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the mnist dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0319
  • Accuracy: 0.9923

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5.0

Training results

Framework versions

  • Transformers 4.22.0.dev0
  • Pytorch 1.12.1+cu102
  • Datasets 2.4.0
  • Tokenizers 0.12.1
Downloads last month
78
Inference API
Drag image file here or click to browse from your device
This model can be loaded on Inference API (serverless).

Dataset used to train farleyknight/mnist-digit-classification-2022-09-04

Space using farleyknight/mnist-digit-classification-2022-09-04 1

Evaluation results